Patent Corpus Mining
Patent Corpus Mining is a computational analysis methodology that systematically extracts, identifies, and interprets patterns, relationships, or novel information from large-scale collections of patent documents to support innovation discovery, technological forecasting, or intellectual property analysis.
138
Publications
7.4K
Citations
444
Authors
207
Institutions
Publications per year
2017–2026
62
Parents
138
1–5 of 138
444
5
h-index
4
h-index
4
h-index
4
h-index
3
h-index
1–5 of 444
207
National Tsing Hua University
Hsinchu, Taiwan
4 h-index
8 publications
504 citations

University of Pisa
Pisa, Italy
4 h-index
15 publications
838 citations
Yonsei University
Seoul, South Korea
4 h-index
9 publications
435 citations

National Yang Ming Chiao Tung University
Hsinchu, Taiwan
4 h-index
5 publications
341 citations

Ajou University
Suwon, South Korea
3 h-index
5 publications
575 citations
Scuola Normale Superiore
Pisa, Italy
3 h-index
3 publications
106 citations
University of Bremen
Bremen, Germany
3 h-index
5 publications
257 citations
Carnegie Mellon University
Pittsburgh, United States
3 h-index
6 publications
274 citations
1–8 of 207
22 publications · 758 citations
15
h-index
11 publications · 884 citations
11
h-index
10 publications · 432 citations
10
h-index
7 publications · 263 citations
7
h-index
4 publications · 267 citations
4
h-index
1–5